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Advantages And Disadvantages Of Cluster Sampling Pdf

advantages and disadvantages of cluster sampling pdf

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Cluster Sampling: Definition, Method and Examples

Cluster sampling is a sampling method where populations are placed into separate groups. A random sample of these groups is then selected to represent a specific population. It is a process which is usually used for market research when there is no feasible way to find information about a population or demographic as a whole. There are 3 requirements which must be met for cluster sampling to be an accurate form of information gathering. Once these requirements are met, there are two types of cluster sampling which can be performed. In single-stage cluster sampling, every element in each cluster selected is used.

What is Cluster Sampling?

Home QuestionPro Products Audience. Cluster sampling is a probability sampling technique where researchers divide the population into multiple groups clusters for research. Researchers then select random groups with a simple random or systematic random sampling technique for data collection and data analysis. Select your respondents. It is impossible to conduct a research study that involves a student in every university.

Despite its benefits, this method still comes with a few drawbacks, including: Biased samples. The method is prone to biases. The flaws of the sample selection. High sampling error. Generally, the samples drawn using the cluster method are prone to higher sampling error than the samples formed using other sampling.

Type of Sampling

Multistage Sampling


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